We’re excited to share that Detectify is one of the vendors featured in KuppingerCole’s Analysts 2026 Leadership Compass on Attack Surface Management. 

Attack surfaces grow every time a team ships code, opens a port, or points a DNS record to a new service. Keeping track of what’s exposed is hard enough, and knowing which of those exposures an attacker can actually use is harder still.

Attack surfaces move at the speed of deployment

AI coding assistants and CI/CD pipelines move code from commit to production in minutes, and new assets reach the internet just as quickly: preview environments, cloud services, APIs and LLM-backed endpoints. For security teams, that means an external attack surface that changes daily and a growing pile of findings to sort through.

Testing with real payloads

Many ASM tools estimate risk from what they can observe passively, such as version strings, banners, and fingerprints. That tells you a server might be vulnerable. It can’t tell you whether the issue is reachable, already patched, or blocked by a WAF, so analysts end up having to confirm each alert by hand.

Detectify takes a different approach. We test exposed assets with real payloads and back each vulnerability we report with the request and response that prove it.

How Detectify approaches ASM

Discovery that keeps up with your infrastructure

Surface Monitoring maps your subdomains, IP addresses, open ports, protocols, technologies and exposed services around the clock, and your DNS and cloud provider connections keep it current. Detectify classifies new assets and recommends where to scan deeper, so they move straight into testing.

Evidence behind every finding

Our scanners send real payloads across external assets, web applications, APIs and AI endpoints, and look for observable evidence that an issue is exploitable. Each finding includes the exact request and response behind it, and Detectify re-tests automatically once a fix is deployed.

Hacker research, scaled with AI

Our tests come from our internal research team, our Crowdsource community of ethical hackers and Alfred, our AI security researcher. Alfred tracks new CVEs, public proof-of-concept code, and threat actor activity, then builds payload-based tests for the vulnerabilities most likely to be exploited.

Where Detectify fits

Detectify is a grear fit for security and AppSec teams who manage a large, fast-changing external attack surface and want findings they can act on right away, especially in fintech, tech, financial services, and the public sector. It connects to the tools those teams already use, from Jira and ServiceNow to Splunk, Slack and CI/CD pipelines, and to AI workflows through our MCP server.

Looking ahead

As attack surfaces grow and more security work is automated, the teams that keep up will be the ones working from findings they can trust. That’s what we build Detectify to deliver: a current view of what’s exposed, and proof of what’s exploitable

See Detectify in action: Book a demo or test your attack surface today with a 2-week free trial.

The post Detectify featured in KuppingerCole’s Analysts 2026 Leadership Compass on Attack Surface Management appeared first on Blog Detectify.

When modern development teams and AI agents ship code at unprecedented speeds, the runtime security checkpoint becomes an indispensable line of defense. However, far too many AppSec teams find themselves drowning in a sea of false positives, overburdened by legacy tools that infer potential vulnerabilities rather than proving their real-world exploitability.

This month, we are proud to announce that Detectify has been positioned as a Major Player in the IDC MarketScape: Worldwide Dynamic Application Security Testing (DAST) 2026 Vendor Assessment (Doc #US54119126, September 2026). In our view, this recognition underscores a fundamental shift occurring across the industry: modern security leaders require verified, actionable intelligence that closes the gap between security policy and operational reality.

The market context

In an increasingly AI-driven development ecosystem where code generation moves faster than human oversight can track, dynamic application security testing (DAST) has transitioned from a routine check to a foundational operational requirement. As engineering teams integrate AI coding assistants into their daily workflows, the sheer volume and velocity of code reaching production increases the probability that subtle security flaws bypass earlier static analysis and design-phase reviews. In this fast-evolving landscape, DAST functions as an essential runtime backstop, continuously evaluating live applications to surface genuine, exploitable risks before malicious actors can discover them.

When software moves to production at such relentless speeds, the precision and exploitability of a security finding matter just as much as how quickly that finding is identified.

The problem with inference

Legacy DAST solutions predominantly rely on passive inference, matching version strings, fingerprinting software stacks, and inferring vulnerabilities based on superficial response headers. While an inferred match might alert you to an outdated component, it fails to determine whether that component is actually reachable, exploitable, or dangerous within your specific environment and data architecture.

This reliance on inference creates a crushing operational burden for security analysts, who are forced to manually triage and re-verify every alert before passing it to engineering teams. When developers receive noisy, unconfirmed alerts, accountability breaks down; conversely, when developers receive payload-verified findings, they take immediate ownership of the fix.

To eliminate this friction, Detectify validates findings through active exploitation rather than passive guesswork. By submitting crafted payloads and requiring observable, confirming evidence (such as out-of-band callbacks or query-disclosing database errors) before an alert is ever generated, Detectify ensures that every reported issue represents demonstrated, actionable risk.

When a finding arrives with definitive proof attached, developers can act immediately without re-investigation or time-consuming alignment meetings.

Three capabilities we built for scale

Validated Exploitation Over Inference

By executing active payloads that require undeniable, observable proof prior to reporting, Detectify transforms vulnerability discovery from a speculative exercise into a high-confidence diagnostic tool. For enterprise AppSec teams managing massive environments, this distinction is critical, as it eliminates the investigative overhead that typically stalls remediation and collapses the delay between vulnerability discovery and resolution.

AI Research That Outpaces Emerging Threats

Rather than waiting for public CVE disclosures to be cataloged, we proactively generate detection modules through Alfred, Detectify’s proprietary AI research agent. Alfred continuously analyzes threat intelligence feeds and hacker-submitted proofs of concept, converting novel exploit techniques into production-ready scanning engines long before they hit traditional databases. This intelligence is complemented by an adaptive ML-trained fuzzer that tailors payload selection specifically to each organization’s unique technology stack based on historical environmental data.

Automated Discovery That Scales with Your Attack Surface

As organizations expand, their external attack surface continuously shifts through new subdomains, cloud deployments, corporate acquisitions, and shadow IT. Traditional tools demand constant manual configuration to keep pace with these changes, creating administrative overhead that compounds as the business grows. Detectify solves this through Surface Monitoring, which automatically discovers, deduplicates, and promotes newly exposed assets into scannable targets without requiring human intervention, allowing security coverage to scale effortlessly alongside your expanding digital footprint.

Who this matters for

This capability model is built specifically for organizations operating centralized, AppSec-led security programs that need to oversee broad and constantly shifting attack surfaces. By automating asset discovery and enforcing strict payload validation, Detectify allows enterprise security leaders to maintain complete visibility and continuous testing across their environments without ballooning operational costs or adding friction to developer workflows.

What this means

As application architectures become more complex and development speeds continue to accelerate, static and inference-based security testing models are reaching their natural limits. We believe our recognition as a Major Player in the 2026 IDC MarketScape for DAST reflects this broader market transition toward continuous, payload-verified validation. Modern security programs do not need more alert volume; they need precise intelligence that proves real-world risk, scales automatically with organizational growth, and empowers teams to protect their applications with confidence.

Ready to see Detectify in action? Book a demo with our application security experts to explore a tailored walk-through.
Want to test your attack surface today? Start a free trial and instantly map your external assets with zero friction.

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